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About Us:
At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta Py Torch and Google Vertex AI.
The Applied Researcher role is designed for engineers who love working across ML, systems, and real-world products, and thrive on working directly with customers to bring advanced models into production.
About the Role
As an Applied Researcher, you will sit at the intersection of ML research, systems engineering, and customer-facing problem solving. You’ll work hands-on with customers and customer data to tune, evaluate and deploy models using various techniques such as SFT / DPO / RL, to help customers build competitive models using their unique data tailored to their unique products.
You will be the technical bridge between customer needs, customer data, and our tuning and serving infrastructure, helping shape the future of applied AI.
Minimum Qualifications
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BS/MS in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent practical experience, open to all levels of experiences.
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Strong experience with Py Torch and modern Transformer architectures.
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Solid computer science fundamentals: data structures, algorithms, concurrency, distributed systems, networking.
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Hands-on experience training, fine-tuning, or evaluating machine learning models, preferably LLMs.
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Familiarity with recent developments in the LLM research domain, including model architectures, training methods, and evaluation strategies.
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Passion for partnering with customers: understanding their constraints, co-designing solutions, and iterating based on real-world feedback.
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Curiosity and enthusiasm for exploring a wide range of problem domains and project types - from quick experiments to long-running, complex engagements.
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Ability to operate in a fast-paced, ambiguous environment and drive projects independently.
Preferred Qualifications
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Experience working directly with customers to deliver end-to-end modeling solutions, from understanding their data and product requirements to deploying tuned models in production.
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Strong familiarity with evaluation methodologies for LLMs (benchmarks, custom evals, error analysis).
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Proficiency in diagnosing system-wide problems that hinder customers from achieving desirable outcomes.
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Deep understanding of tuning techniques (SFT, DPO, RL) and the underlying mathematical principles.
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Knowledge of infrastructural components that enterprises commonly use, such as databricks, S3/GCS storage, Sage Maker, artifact registry etc
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Familiarity with cloud-native tooling (containers, Docker, Kubernetes, or similar).
Why Fireworks AI?
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Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
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Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
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Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
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Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
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About Fireworks AI

Fireworks AI
Series AFireworks AI provides generative AI inference and fine-tuning platform for developers and enterprises. The company offers high-performance API services for running large language models and other generative AI workloads.
51-200
Employees
San Francisco
Headquarters
$1.2B
Valuation
Reviews
3.8
26 reviews
Work Life Balance
3.5
Compensation
4.2
Culture
3.8
Career
4.0
Management
3.6
79%
Recommend to a Friend
Pros
Supportive team and management
Opportunity for career growth
Interesting projects and challenges
Cons
Internal communication could improve
Career progression could be clearer
Work-life balance varies by team
Interview Experience
43 interviews
Difficulty
3.1
/ 5
Duration
14-28 weeks
Offer Rate
41%
Experience
Positive 60%
Neutral 21%
Negative 19%
Interview Process
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
Common Questions
Technical skills
Past experience
Team collaboration
Problem solving
News & Buzz
Fireworks AI Positions Open-Source Infrastructure as Low-Cost, Privacy-Focused Backbone for Personal AI Agents - TipRanks
Source: TipRanks
News
·
5w ago
This CEO left Meta and built a $4B AI startup by rejecting the one-size-fits-all approach - The Business Journals
Source: The Business Journals
News
·
8w ago
Fireworks, Metropolis and Hippocratic AI Lead Funding Rounds - PYMNTS.com
Source: PYMNTS.com
News
·
17w ago
Fireworks AI raises $250M at $4B valuation to help enterprises with AI inference workloads - SiliconANGLE
Source: SiliconANGLE
News
·
18w ago

